Pharmacophore modeling and virtual screening in search of novel Bruton’s tyrosine kinase inhibitors

  • Aditya Sharma
  • B. K. ThelmaEmail author
Original Paper


Bruton’s tyrosine kinase (BTK) is a known drug target for B cell malignancies and autoimmune diseases like rheumatoid arthritis. Consequently, efforts to develop BTK inhibitors have gained momentum in the last decade, resulting in a number of potential inhibitory molecules. However, to date, there are only two FDA approved drugs for B cell malignancies (Ibrutinib and Acalabrutinib), thus continued efforts are warranted. A large number of molecular scaffolds with potential BTK inhibitory activity are already available from these studies, and therefore we employed a ligand-based approach towards computer-aided drug design to develop a pharmacophore model for BTK inhibitors. Using over 400 molecules with known half maximal inhibitory concentrations (IC50) for BTK, a four-point pharmacophore hypothesis was derived, with two aromatic rings (R), one hydrogen bond acceptor (A) and one hydrogen bond donor (D). Screening of two small-molecule databases against this pharmacophore returned 620 hits with matching chemical features. Docking these against the ATP-binding site of the BTK kinase domain through a virtual screening workflow yielded 30 hits from which ultimately two natural compounds (two best scoring poses for each) were prioritized. Molecular dynamics simulations of these four docked complexes confirmed the stability of protein–ligand binding over a 200 ns time period, and thus their suitability for lead molecule development with further optimization and experimental testing. Of note, the pharmacophore model developed in this study would also be further useful for de novo drug design and virtual screening efforts on a larger scale.

Graphical abstract

Pharmacophore modeling and virtual screening in search of novel Bruton’s tyrosine kinase inhibitors


Bruton’s tyrosine kinase BTK inhibitors Pharmacophore modeling Virtual screening Molecular dynamics simulations 



Grant# BT/COE/34/SP15246/2015 (Phase II) to BKT from the Department of Biotechnology, Government of India, New Delhi, India and Junior and Senior Research Fellowship from the Department of Genetics, University of Delhi South Campus under UGC-Special Assistance Program Meritorious Award scheme to AS are gratefully acknowledged. We are thankful to Schrödinger, Inc., India for providing an evaluation license for Schrödinger software suite (2017, v2017-2) to carry out this study. We also gratefully acknowledge infrastructure support provided by the UGC, New Delhi, through Special Assistance Programme and Department of Science and Technology, New Delhi, through FIST and DU-DST PURSE programmes to the Department of Genetics, UDSC. The authors would like to extend their gratitude to Dr. N. Latha, Associate Professor, Department of Biochemistry and Coordinator, Bioinformatics Centre, Sri Venkateswara College, University of Delhi for providing infrastructure support and critical inputs for this study.


BKT and AS designed the study; AS performed the computational analysis; AS and BKT wrote the manuscript and both have approved the final manuscript.

Compliance with ethical standards

Declarations of interest


Supplementary material

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Authors and Affiliations

  1. 1.Department of GeneticsUniversity of Delhi South CampusNew DelhiIndia

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